Model-based system tool for Thai Tax Revenue Forecasting (MBS-TTRF)

J. Mitrpanont, Pattama Tounprasert
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引用次数: 3

Abstract

Model-Based System Tool for Thai Tax Revenue Forecasting (MBS-TTRF) is a model-based management system used to provide the flexibility and increase efficiency of Thai Tax Revenue Forecasting in the Revenue Department (RD). MBSTTRF contains five essential model-categories for Tax Revenue Forecasting, i.e., ETTRF Models, NITTRF Models, STTRF Models, TTRF A Models, and TTRFAC Models. The system supports the data analytical functions: Sensitivity, What-if and Goal-seeking analysis, useful for analyzing results before making a decision. Furthermore, this system also improves the accuracy of Thai Tax Revenue Forecasting by adding regression approach to NITTRF. The experimental results showed that NITTRF generated better results than the existing model-ETTRF. The results also showed that MBS-TTRF is suitable to assist a user/decision maker as an alternative model to forecast tax revenue and reduces time for Thai Tax Revenue Forecasting operation that depends mainly on human expertise.
基于模型的泰国税收预测系统工具(MBS-TTRF)
基于模型的泰国税收预测系统工具(mbs - trf)是一个基于模型的管理系统,用于提供灵活性和提高泰国税收预测在税务局(RD)的效率。MBSTTRF包含税收预测的五个基本模型类别,即ETTRF模型、NITTRF模型、STTRF模型、TTRFA模型和TTRFAC模型。系统支持数据分析功能:敏感性分析、What-if分析和目标寻求分析,有助于分析结果再做出决策。此外,该系统还通过在NITTRF中加入回归方法,提高了泰国税收预测的准确性。实验结果表明,NITTRF比现有的ettrf模型产生了更好的结果。结果还表明,MBS-TTRF适合作为辅助用户/决策者预测税收的替代模型,并减少主要依赖于人类专业知识的泰国税收预测操作的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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